Thesis Abstract

The abstract is a comprehensive summary of the main points of the thesis, providing a clear overview of the research conducted, the methods employed, and the findings obtained. Below is an abstract for the thesis titled "Analysis of landslide susceptibility in a specific region using GIS and remote sensing techniques." Abstract
Landslides are natural hazards that pose significant risks to human lives, infrastructure, and the environment. Understanding the factors contributing to landslide susceptibility is crucial for effective risk assessment and mitigation strategies. This thesis focuses on the analysis of landslide susceptibility in a specific region through the integration of Geographic Information Systems (GIS) and remote sensing techniques. The study area, located in [specific region], has experienced recurrent landslide events, highlighting the urgent need for a comprehensive analysis to assess susceptibility factors and guide land use planning decisions. The research begins with a detailed review of existing literature on landslide susceptibility assessment methods, GIS applications, and remote sensing technologies. Through a systematic literature review, key factors influencing landslide occurrence, such as topography, geology, land cover, and rainfall patterns, are identified and analyzed. Additionally, the role of GIS and remote sensing in landslide susceptibility mapping is explored, emphasizing their potential to enhance spatial analysis and modeling capabilities. The methodology chapter outlines the research design, data collection procedures, and analytical techniques employed in the study. High-resolution satellite imagery, digital elevation models, and geological maps are utilized to extract relevant spatial data for landslide susceptibility mapping. GIS-based models, such as the Analytical Hierarchy Process (AHP) and Logistic Regression, are applied to integrate multiple factors and generate susceptibility maps for the study area. The validation of the models is conducted using historical landslide records and field surveys to assess the accuracy and reliability of the results. The findings chapter presents the results of the analysis, highlighting the spatial distribution of landslide susceptibility zones in the study area. The susceptibility maps generated through GIS and remote sensing techniques reveal areas at high, moderate, and low risk of landslide occurrence based on the identified factors. The influence of topographic features, land cover types, and geological characteristics on landslide susceptibility is examined, providing valuable insights for land management and disaster preparedness. In conclusion, this thesis contributes to the understanding of landslide susceptibility assessment in the specific region by utilizing advanced GIS and remote sensing tools. The integration of spatial data and analytical models enables the identification of vulnerable areas and the prioritization of mitigation measures to reduce landslide risks. The significance of this research lies in its practical implications for land use planning, disaster risk reduction, and sustainable development in landslide-prone regions. Keywords Landslide susceptibility, Geographic Information Systems (GIS), Remote sensing, Analytical Hierarchy Process (AHP), Logistic Regression, Risk assessment, Spatial analysis, Disaster management, Sustainable development.

Thesis Overview

The project titled "Analysis of landslide susceptibility in a specific region using GIS and remote sensing techniques" focuses on the application of advanced geospatial technologies to assess the potential for landslides in a particular region. Landslides pose significant threats to infrastructure, human lives, and the environment, making their identification and analysis crucial for effective risk management and mitigation strategies. Geographic Information Systems (GIS) and remote sensing have emerged as powerful tools in landslide susceptibility mapping due to their ability to integrate various spatial datasets, analyze terrain characteristics, and visualize potential hazard zones. This project seeks to leverage the capabilities of GIS and remote sensing to conduct a comprehensive analysis of landslide susceptibility in a specific region, with the aim of identifying high-risk areas and providing valuable insights for disaster preparedness and land-use planning. The research will begin with a detailed review of existing literature on landslide susceptibility mapping, GIS techniques, remote sensing applications, and relevant case studies. This literature review will provide a solid theoretical foundation for understanding the methodologies and approaches commonly used in landslide analysis and mapping. The project will then proceed to collect and preprocess spatial data, including digital elevation models, land cover maps, rainfall data, and geological information. These datasets will be utilized to extract terrain attributes, such as slope, aspect, elevation, and land cover characteristics, which are known to influence landslide occurrence. Using GIS software, spatial analysis techniques will be applied to develop a landslide susceptibility model based on a combination of terrain attributes and historical landslide occurrences. The model will be validated using statistical methods and spatial accuracy assessments to ensure its reliability and robustness. In parallel, remote sensing data, such as aerial imagery and satellite images, will be used to monitor land surface changes, detect potential landslide precursors, and assess the impact of environmental variables on slope stability. Remote sensing techniques, including image classification, change detection, and feature extraction, will be employed to enhance the understanding of landscape dynamics and identify areas prone to landslides. The findings of this research will be presented through thematic maps, spatial visualizations, and statistical analyses to delineate areas of high, moderate, and low landslide susceptibility in the study region. The implications of these findings will be discussed in the context of hazard mitigation strategies, urban planning, and disaster risk reduction efforts. In conclusion, this project aims to contribute to the field of geohazards management by demonstrating the effectiveness of GIS and remote sensing technologies in assessing landslide susceptibility and providing valuable insights for decision-makers and stakeholders. By combining spatial analysis, terrain modeling, and remote sensing data, this research endeavors to enhance our understanding of landslide dynamics and support proactive measures to minimize the impact of landslides in vulnerable regions.